NSF awards $83 million to expand data infrastructure for AI-driven scientific research
The National Science Foundation announced $83 million in awards on July 22, 2026, for an initiative intended to connect scientific data with computing, instruments, software and artificial-intelligence resources.
The awards were made through NSF’s Integrated Data Systems and Services program. The effort is designed to expand access to data infrastructure that researchers can use alongside advanced computing and AI systems, potentially increasing the capacity of federally supported research.
Building connections between data and computing
Scientific research increasingly depends on more than the data collected in a laboratory, field study or instrument. Researchers also need ways to store, organize, share and analyze that information using computing resources, software and specialized tools.
NSF said the new investments will connect those pieces. The program links scientific data with computing, instruments, software and AI resources, creating infrastructure intended to make large datasets easier to access and use.
That approach could help research teams work with data in more integrated ways and support discovery across scientific fields. The stated purpose of the investment is to expand research capacity; it is not an announcement that specific scientific discoveries have already been produced.
NSF said the initiative complements the National Artificial Intelligence Research Resource, along with other cyberinfrastructure investments. The relationship places the new awards within a broader federal effort to provide researchers with tools for AI-related work rather than treating data systems as separate from computing and research infrastructure.
Named project will create a national data fabric
One of the projects identified by NSF is Fabric for AI-Driven Science, led by the Morgridge Institute for Research in Madison, Wisconsin.
The project will build a national data fabric connecting repositories, computing resources and cyberinfrastructure. In practical terms, the planned system is intended to link places where scientific data are stored with the computing and digital systems researchers use to work with that information.
The project’s focus reflects the central challenge addressed by the broader program: scientific data can be valuable for AI and other forms of computation only when researchers can find it, access it and use it with appropriate technical resources. A connected infrastructure can provide a foundation for that work, although the announcement does not establish when all funded systems will become operational.
The NSF announcement also does not identify the complete list of award recipients or how the $83 million will be divided among individual projects. Those details will determine the scale and reach of each investment, but the agency’s announcement establishes the overall funding commitment and the program’s infrastructure focus.
Part of U.S. AI and research strategy
NSF said the investments support national priorities involving U.S. leadership in artificial intelligence, development of an AI-ready workforce and research tools intended to improve global competitiveness.
For researchers, the practical significance is access to systems that can bring data, computing and software closer together. Better-connected infrastructure may reduce technical barriers to working with large scientific datasets and make federally supported research resources more useful across projects.
The investment also reflects a policy choice to support the underlying systems needed for AI-driven science. Rather than focusing only on individual applications, the program targets shared data and cyberinfrastructure that can serve as a base for research and workforce development.
NSF has announced the awards, but the public announcement does not quantify expected scientific outputs or specify a single date when the full set of systems will be available. The next phase is the development and implementation of the funded projects, including the national data fabric led by the Morgridge Institute for Research.
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